This application is related to the following copending U.S. applications: xe2x80x9cMethod and Apparatus for Associating Retail Performance Metrics with Individual Entries and/or Time Type Categoriesxe2x80x9d for Michael J. Matsko and Katherine R. Lehman and xe2x80x9cMethod and Apparatus for Storing Retail Performance Metricsxe2x80x9d for Michael J. Matsko; all the above applications being filed concurrently herewith.
The present invention relates generally to a method and apparatus for determining a retail performance metric of entry identification time, and more particularly, to such a method and apparatus wherein the entry identification time is determined as a function of elapsed time between when a point of sale (POS) terminal starts waiting for new input and when the point of sale terminal receives an entry of new input.
Retail store managers continually monitor individual point of sale (POS) terminal and POS terminal operator, or clerk performance for areas of improvement and error or problem detection and identification. Poor performance by either terminal or clerk impacts the overall profitability of the store. One method of monitoring is to record timing information about the clerk and POS terminal during job performance. Several approaches are available to record timing information, such as 1) software or hardware based automated time recording or 2) direct or videotaped observation and human factors engineering and analysis.
Under the first approach identified above, i.e., automated time recording, the POS terminal software records timing information about the clerk and events occurring at the terminal. However, typical retail POS terminal software retains only a small set of the overall timing information. Most POS terminal software retains calculations of time for all entries in a transaction log categorized in one of six time type categories: ring time, tender time, secure time, non-sales time, idle time, and no time.
Ring time is the time spent itemizing, scanning, keying in or selling items to customers.
Tender time is the time spent by a clerk or POS terminal receiving payments from customers.
Secure time is the time the POS terminal is locked or otherwise signed-on but secured.
Non-sales time is the time spent by a clerk performing activities unrelated to selling items, or tendering payment from customers, such as pricing inquiries or terminal behavior option modifications.
Idle time is the time spent during the period of activity between transactions and before the first transaction after signing on to the terminal.
No time is the time during which the terminal is signed off and not in use by a clerk.
Any and all recorded occurrences at the POS terminal are categorized into one of these six time type categories. Categories may be added, subtracted or modified as necessary or as dictated by the configuration of the store. As a result of this type of time measurement, only a portion of the time spent in each of the categories is under direct control of the POS terminal operator. For example, the operator controls how quickly items are scanned and tenders are inputted but has no control over other actions that contribute to these time measurements. Such additional factors contributing to the time measurements include the bar code quality in the product mix presented to the operator, the types of error warning levels configured in the store, the POS terminal scanner quality, and the various tender validation requirements active at the store. For example, a store may have a policy requiring all checks being presented to be accompanied by at least two pieces of identification, or the bar code on certain products may not be of the same quality as other products and may require multiple scan attempts or keyed input for entry of the product. The additional time required is unable to be separated from the category times and viewed or analyzed independently from the defined categories. Thus, there is a need in the art to enable tracking of individual occurrences within the defined time type categories.
Another problem identified in prior art systems is that the granularity of the timing information is very broad, i.e., typically the timing information is written to the transaction log (TLOG) as a single record with summarized totals for an entire transaction. Each transaction in the transaction log records the interaction of the operator and/or POS terminal with a customer and includes transaction entries recording events indicative of occurrences during the transaction. The transaction events include xe2x80x9cscanxe2x80x9d indicating a product bar code scan, xe2x80x9ckeyxe2x80x9d indicating a product identification using an input device, usually a keyboard, and xe2x80x9ctenderxe2x80x9d indicating a customer providing payment. There are additional types of transaction events known in the art. Typically, a transaction entry in the transaction log includes a terminal identifier, an operator identifier, an event type, and an indication of the items purchased by the customer, if applicable. However, timing information, if recorded, is stored in the summarized time type category totals.
For example, if the operator spends three periods of time in ring time and two periods of time in secure time during a transaction, the transaction log will only reflect the total for each of the periods of time spent by the operator in secure time and ring time, but not the individual amount of time spent in each of the secure time or ring time periods for each entry or event during a transaction. In other words, if the three periods of ring time include a ten second period, a twelve second period, and a fifteen minute period, the transaction log will indicate a ring time of fifteen minutes and twenty-two seconds, possibly indicating an operator with a high ring time. In fact, the fifteen minute period may be due to operator or system errors, but is less likely to be discovered using prior approaches. Thus, to provide more accurate indications of efficiencies, and conversely, inefficiencies, there is a need in the art to enable logging of individual time period occurrences within the defined categories and/or individual transactions.
As retailers become more concerned with increasing overall system performance, increasing profits and lowering costs, it is more important to separate the high-level time measurements or time summaries of the time type categories into the individual components making up the summaries. An important portion of this time occurs during the time period when the operator is commanding the POS terminal to do something such as add a product to a customer""s purchase order or determine the weight of an item on a scale, otherwise known as the xe2x80x9centry identificationxe2x80x9d time. As used in this specification, entry identification time is the time period during which the POS terminal waits for operator input and the operator inputs a particular entry into the POS terminal or tells the POS terminal to do something. The entry identification time is the time period over which the operator has the greatest amount of control and the one that most correctly measures operator performance. Thus, there is a need in the art to track a performance metric known as entry identification time.
As identified above, the second approach to solving these problems is to apply industrial or human factors engineering methods to obtain and analyze operator and POS terminal performance. These methods include time-and-motion analysis, video task analysis, and stop-watch measurements. Human factors engineering companies offer services to retailers, such as performing video data collection and task analysis on front-end check out operations. The data collected aids human factors engineers to quantify the productivity of the operator and POS terminal, identify bottlenecks, and make recommendations for POS terminal or check stand design, process changes, and technology to improve productivity. Because the human factors engineering methodology provides detailed, accurate, and quantifiable data, cost-benefit calculations can be made to demonstrate the financial impact of implementing a recommendation.
However, industrial engineering approaches and human factors engineering analysis techniques have a number of limitations. For instance, the techniques are labor intensive and costly for retailers. In order to obtain statistically valid results, a large data sample is required necessitating many hours of costly observation and analysis.
Due to the cost, typically only a small sample of data (ranging from approximately a few hours to one week""s worth) is collected resulting in insufficient sample sizes which negatively affects statistical validity, interpretation of the data and quality of the results. Continuous data collection over months or years, desirable for longitudinal studies (e.g., long-term trend analysis) is cost prohibitive. The potential for human error is inherent in this type of data collection and analysis.
Thus, there exists a need in the art for a method to provide automatic, continuous, consistent, and detailed data capture of entry identification times. Any solution must capture timing information for each individual action of interest.
Accordingly, an object of the present invention is to track a retail performance metric known as entry identification time.
Another object of the present invention is to track individual RPM occurrences with defined categories at a POS terminal.
Another object of the present invention is to track individual RPM occurrences with transactions at a POS terminal.
Another object of the present invention is to track individual RPM occurrences with transaction entries at a POS terminal.
Another object of the present invention is to provide automatic, continuous, consistent, and detailed data capture of entry identification times.
The present invention provides a method and apparatus for determining a retail performance metric of entry identification time. The entry identification time is determined by recording the time the system waited for and received an input. The retail performance metric type is determined as a function of the input received by the system. A retail performance metric record is recorded as a function of the time elapsed waiting for and receiving an input and the retail performance metric type.
In accordance with a method aspect of the invention, a computer system waits for an input. Upon receiving the input, the system determines the retail performance metric type of the input received and determines a retail performance metric which is the time elapsed waiting for and receiving an input. The system records a retail performance metric record which is a function of the retail performance metric type and the retail performance metric.
Another aspect of the invention relates to a computer system comprising a processor and a memory coupled to the processor. The memory stores sequences of instructions which, when executed by the processor, cause the processor to wait for an input. Upon receiving the input, the processor determines the retail performance metric type of the input received, determines the retail performance metric which is the time elapsed waiting for and receiving the input, and records a retail performance metric record. The retail performance metric record is a function of the retail performance metric type and the retail performance metric.